|
|
Absolute deviation, 绝对离差+ X, ^* C2 t0 y$ s) J f
Absolute number, 绝对数
0 k# O$ R1 X3 U/ X' ^Absolute residuals, 绝对残差
8 {" w2 u5 ?6 Q) O* D* E& AAcceleration array, 加速度立体阵# k, m R* {9 n* }
Acceleration in an arbitrary direction, 任意方向上的加速度
! G+ X5 {& O% v+ K1 OAcceleration normal, 法向加速度
5 W! [' F6 v2 t. l0 CAcceleration space dimension, 加速度空间的维数: M' a/ W& K7 q3 Q, t
Acceleration tangential, 切向加速度, x X/ ?! B+ |2 B
Acceleration vector, 加速度向量
( j& r; r( q: S( @+ B' I( J, y! w$ AAcceptable hypothesis, 可接受假设; r/ U% ]: k! c+ E
Accumulation, 累积
+ h+ U. G6 B- JAccuracy, 准确度
8 G/ q5 j4 \7 ?, @' R5 T" n8 U) hActual frequency, 实际频数
0 o( s) Z' U; sAdaptive estimator, 自适应估计量
9 K% G& [: V- PAddition, 相加2 ]7 B5 e" [) X# ]# x2 V
Addition theorem, 加法定理
* c+ u& {6 q/ ?0 [1 B1 ~6 Z6 o. LAdditivity, 可加性# g" i& n/ [8 w. Y
Adjusted rate, 调整率" x3 O$ }+ V: _/ b: U
Adjusted value, 校正值1 N7 j! q( c m, G+ c% |3 c/ ]* Y8 c
Admissible error, 容许误差9 l, J/ @7 g& n6 Y$ p
Aggregation, 聚集性' x6 y, G, a i
Alternative hypothesis, 备择假设
6 q6 B5 @+ a! z! r6 N% D2 t* b2 L, ZAmong groups, 组间
: g# l- h. j5 b4 x/ W! c( T( x2 z! @Amounts, 总量
7 e) i% W+ ~+ `/ l9 Y: E! kAnalysis of correlation, 相关分析7 J) E1 E% L% T# \$ c
Analysis of covariance, 协方差分析# `( @5 ?9 F2 k0 [
Analysis of regression, 回归分析
) I6 d$ g9 e+ Y) M5 H, E8 V4 v oAnalysis of time series, 时间序列分析
* y) k& ]7 }( A( D2 u1 iAnalysis of variance, 方差分析9 _3 S; n X4 c9 n! I- W1 h5 b
Angular transformation, 角转换, n3 d$ h) X. I0 ]" p
ANOVA (analysis of variance), 方差分析
. ? A. X/ S8 O! [ANOVA Models, 方差分析模型
! M4 V' X3 u0 T5 ?' V! z4 F% dArcing, 弧/弧旋5 P' s% l+ J0 S" F S8 U
Arcsine transformation, 反正弦变换
6 p, o2 R s' I: J: M9 H8 eArea under the curve, 曲线面积
+ h5 V; q) ^1 IAREG , 评估从一个时间点到下一个时间点回归相关时的误差
1 F/ l# i* ^' k- SARIMA, 季节和非季节性单变量模型的极大似然估计
3 k8 s* K p5 {/ A B" G, q% }Arithmetic grid paper, 算术格纸7 u1 h/ {9 V; V4 [
Arithmetic mean, 算术平均数2 ~$ ~: Q4 b% A! b+ O# ~
Arrhenius relation, 艾恩尼斯关系- A* J5 S, R! L! ^+ U
Assessing fit, 拟合的评估% f- o4 o' L E, O: V
Associative laws, 结合律
, V3 L) ^* X& E/ fAsymmetric distribution, 非对称分布6 D: E: {& i( E. B; T* h" u4 m- f
Asymptotic bias, 渐近偏倚4 b2 p, d; f# x8 f _
Asymptotic efficiency, 渐近效率4 i0 ~2 X* q/ V) a; q; q- d
Asymptotic variance, 渐近方差( Q5 S& J# k* l3 C9 A% x- a& R! A
Attributable risk, 归因危险度+ P. H; N' s2 ~/ o+ G
Attribute data, 属性资料1 t! G7 d. E: W6 d* X& K' z
Attribution, 属性
/ G0 H3 h* n) q7 I1 SAutocorrelation, 自相关, l" G8 a# Q5 x
Autocorrelation of residuals, 残差的自相关! n- g+ t# `" A6 g; M
Average, 平均数; D5 `9 ]9 r I; n
Average confidence interval length, 平均置信区间长度
3 C) f! ~5 o9 ], m3 nAverage growth rate, 平均增长率5 c7 p1 @# v" t. Y) \* J7 v
Bar chart, 条形图
}* `$ M, w4 Q y: E9 EBar graph, 条形图
* [, [. U5 o, nBase period, 基期! n" j4 |! e- n- f. O+ ?
Bayes' theorem , Bayes定理
9 I! a7 |5 z- e; @: }Bell-shaped curve, 钟形曲线2 o1 m* K# W7 E+ R0 z. D+ G% v' ~2 h
Bernoulli distribution, 伯努力分布, ^0 K8 @8 B d H) Z: o
Best-trim estimator, 最好切尾估计量
( ]5 i9 \8 y; o) f; g2 v: C: k- [2 c3 xBias, 偏性9 ?7 ?7 m; s$ B; N
Binary logistic regression, 二元逻辑斯蒂回归
% h! [1 r& l+ y- U- e* ~Binomial distribution, 二项分布
9 B4 k$ Y j: V" e9 p, Z( x, tBisquare, 双平方5 v, D1 ]3 c% ?# u1 a7 E
Bivariate Correlate, 二变量相关: H. t0 a7 p9 a
Bivariate normal distribution, 双变量正态分布
7 U; R# U8 G8 ~7 `0 rBivariate normal population, 双变量正态总体
# \) T( g* L& F- Z# p3 M! YBiweight interval, 双权区间
1 ?9 Q* f& E) Y# v/ Z yBiweight M-estimator, 双权M估计量
, W* m. i1 q" U) QBlock, 区组/配伍组
+ O4 G5 ]( A8 n( V5 ZBMDP(Biomedical computer programs), BMDP统计软件包( t% g2 j+ u0 l. L( ^' W
Boxplots, 箱线图/箱尾图
: q2 X0 r- e$ FBreakdown bound, 崩溃界/崩溃点
8 E) P9 @( o m' U% `- \7 QCanonical correlation, 典型相关& ?7 S" b5 [; h
Caption, 纵标目
! o$ _1 l9 R3 i6 q( [) u ]( ICase-control study, 病例对照研究4 h( D/ }4 e5 Q( U7 R
Categorical variable, 分类变量
1 y+ \% v) Y& MCatenary, 悬链线
6 S, V0 P. W. Y0 C+ _8 h3 rCauchy distribution, 柯西分布
* W7 l1 [- `1 U) B4 s" LCause-and-effect relationship, 因果关系2 R2 b' \7 R1 [$ m1 \
Cell, 单元5 @& D6 e8 s& ^+ m0 T
Censoring, 终检
l% e' T+ r( FCenter of symmetry, 对称中心
1 G! u% R0 g# J$ F1 d x/ h x( eCentering and scaling, 中心化和定标# X! I) Y( V) a. m5 \
Central tendency, 集中趋势+ O1 D! ~. S7 `3 u$ e9 t
Central value, 中心值
8 p0 K. Q. ]- F4 m RCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
, J- \6 @1 o3 i8 h6 LChance, 机遇9 w2 m$ a( C2 Y$ G$ n( d X
Chance error, 随机误差
# i" F7 C& ~: K( p9 h P* k" EChance variable, 随机变量 D5 r+ I$ ?$ E6 X: J' k
Characteristic equation, 特征方程
" Q8 t' W& ~1 \7 Q4 }- N( QCharacteristic root, 特征根6 Z8 p) z* y; E* e8 q: {- {; e+ {
Characteristic vector, 特征向量
- f) ]0 v x6 ?+ U: i8 RChebshev criterion of fit, 拟合的切比雪夫准则
: _) P% I9 Q! \5 q8 W, ~! @Chernoff faces, 切尔诺夫脸谱图. Y7 v" k8 ^% s' k6 K& ~/ Z
Chi-square test, 卡方检验/χ2检验7 \6 ?6 j3 Q( ]7 O" o Z) r3 E
Choleskey decomposition, 乔洛斯基分解
* P6 Y2 K! s! H- g7 _3 y$ ICircle chart, 圆图 4 b& N% s$ y+ ]( s
Class interval, 组距
$ o* u" Y: o- _! F1 b3 V- KClass mid-value, 组中值( A, C) S) P/ ?. q/ r% I, h1 O
Class upper limit, 组上限8 {' N7 P5 ~! M6 T5 ~% [( {/ c
Classified variable, 分类变量
3 X0 h5 t6 A# t5 [Cluster analysis, 聚类分析 ^* H) |7 l! @ h
Cluster sampling, 整群抽样6 v3 P ~4 W( I/ ~3 C
Code, 代码2 h e9 d" W6 @8 v
Coded data, 编码数据
' B) `1 K# b8 c% QCoding, 编码: D" G( g# @/ z( u+ s) e4 H
Coefficient of contingency, 列联系数( }2 P K) m$ h
Coefficient of determination, 决定系数
# A+ x9 C" i2 l. \1 {, pCoefficient of multiple correlation, 多重相关系数
( y' P2 t3 j# z( G7 R' q& jCoefficient of partial correlation, 偏相关系数
$ F, I, w& D; J' [' l# uCoefficient of production-moment correlation, 积差相关系数
) s) A6 w/ }5 c6 q5 H) d5 l6 z- dCoefficient of rank correlation, 等级相关系数! w! {7 i( l6 q; V
Coefficient of regression, 回归系数
8 G0 i0 {! F# Z9 S. t4 U# fCoefficient of skewness, 偏度系数
" k% a1 p# H: @9 ~+ F' aCoefficient of variation, 变异系数
& q/ m7 m8 H& [( R! J$ i& h' QCohort study, 队列研究
9 ^ X. @) m& I7 t4 K" XColumn, 列; C, V/ l# @" e$ o2 C' x
Column effect, 列效应
' S) ]+ S( @' Z5 hColumn factor, 列因素
' u! t7 x! \" ], aCombination pool, 合并
# f5 t. g+ i. Y% M( W" WCombinative table, 组合表( x2 n2 b K( Z8 L6 m+ v
Common factor, 共性因子" c# Z, M, z! q' q2 x& q
Common regression coefficient, 公共回归系数
% Z0 V1 Q; X; ?6 ?7 vCommon value, 共同值+ }# J; p* O# K: W
Common variance, 公共方差
( O4 H0 U) L2 \0 gCommon variation, 公共变异4 E3 X& H1 T; P/ H& g9 K2 A8 G
Communality variance, 共性方差7 I$ l& j2 n# e+ x+ y
Comparability, 可比性
& d" X0 S5 k5 ?Comparison of bathes, 批比较6 B' ]8 a- i3 F2 {1 w: J6 S
Comparison value, 比较值( j: g- @9 v- d. A8 E8 w" b
Compartment model, 分部模型4 C" p! S% U6 {
Compassion, 伸缩5 L) T7 p/ l l& R z( z" E
Complement of an event, 补事件
/ P% b4 Q K. ~0 x: g7 A q! A( UComplete association, 完全正相关
" Y {. W; p1 j+ Q) OComplete dissociation, 完全不相关0 S$ P! i6 b/ R1 w6 q- o
Complete statistics, 完备统计量" N& R2 |4 q; L2 F7 F' K$ ]
Completely randomized design, 完全随机化设计6 j. U7 q. h U8 K' c- [* F
Composite event, 联合事件
$ t1 @5 m! x* U* q7 N; W/ AComposite events, 复合事件5 w2 i% D5 s; |7 p3 i3 A
Concavity, 凹性 w8 [/ J, x; P( E4 N/ Z
Conditional expectation, 条件期望& E4 T8 d/ |6 E2 u+ O1 x
Conditional likelihood, 条件似然
7 f. Z8 O7 o! KConditional probability, 条件概率
! n6 ?) p/ _' n O2 jConditionally linear, 依条件线性
1 k- T6 H: }; z$ V6 j& C3 KConfidence interval, 置信区间
/ }5 R4 o$ z* T8 w; QConfidence limit, 置信限
I3 u# X+ a" ^5 }Confidence lower limit, 置信下限8 U# B# H. K. S( p, \: G, F
Confidence upper limit, 置信上限
& O, ]' V7 C; N% h: `5 Q1 lConfirmatory Factor Analysis , 验证性因子分析( q7 y0 A- O' q3 ~1 i
Confirmatory research, 证实性实验研究
' b" E- X- b' b9 G: Z; dConfounding factor, 混杂因素
# k. L1 }% P. [) e' @Conjoint, 联合分析
2 r0 W5 h3 [6 @) m5 PConsistency, 相合性
7 n- ]& ~* X9 oConsistency check, 一致性检验2 L5 Q- |# p# ?0 d0 m, P( \! h
Consistent asymptotically normal estimate, 相合渐近正态估计
8 ^" e# s" l6 @/ i& c, R; d: l. FConsistent estimate, 相合估计: r+ ~- ~. ], M4 ]2 d6 E0 R. g
Constrained nonlinear regression, 受约束非线性回归
' `) E2 u5 L9 F! x. i' o- y) XConstraint, 约束1 g/ e4 H$ M9 H! b* Y& d$ d, c
Contaminated distribution, 污染分布. x7 d8 z& l+ D' Q
Contaminated Gausssian, 污染高斯分布
0 U; X4 \. d0 u; `0 W gContaminated normal distribution, 污染正态分布5 ^; |& p& E$ R, {4 u
Contamination, 污染# W% f7 W+ B/ j) Q
Contamination model, 污染模型
5 x6 N5 V/ g, [1 R9 zContingency table, 列联表# S5 {0 i9 C1 V
Contour, 边界线+ }) J" E0 {7 J) t$ v9 ^8 y
Contribution rate, 贡献率9 `% b' l- I2 x9 i
Control, 对照7 [9 {: q6 N8 }6 D! L. F
Controlled experiments, 对照实验
# ~2 `6 u" q; ]$ x8 XConventional depth, 常规深度
5 ^/ Y* |! h+ ?0 Z9 ^Convolution, 卷积% g1 c c# `+ k4 G7 B- e' V9 k
Corrected factor, 校正因子4 W4 s! B1 O- _# W5 ^3 I7 i
Corrected mean, 校正均值
% a0 \3 L& I$ V3 r3 FCorrection coefficient, 校正系数
' I6 @/ f! r9 c! T% U) h5 ]Correctness, 正确性
# U# i! n/ Q) P8 Z" {Correlation coefficient, 相关系数$ l4 [9 `5 t, e" [0 Z5 A
Correlation index, 相关指数6 ?/ h* G$ v( C/ y" ~3 i- l7 \; W
Correspondence, 对应
# J) K2 k0 V; c6 s. LCounting, 计数/ ]% I( ^. I3 k' U3 C
Counts, 计数/频数
: ~1 ~5 t, |) L; @$ {Covariance, 协方差& l: u6 y3 B: J: I2 r: ?
Covariant, 共变
- I/ c: L+ u8 G W% VCox Regression, Cox回归
' _2 s$ V" o- i, M) g* B2 pCriteria for fitting, 拟合准则
& _+ t4 @+ a: D: ~) BCriteria of least squares, 最小二乘准则4 R0 L2 K4 |/ e) J, J+ \
Critical ratio, 临界比" d9 o" B9 B5 N
Critical region, 拒绝域
, x, T% P O" g" {5 UCritical value, 临界值
9 b- [! O( c1 g0 i/ i& l6 X6 RCross-over design, 交叉设计
V' C# X2 _: u/ r d3 NCross-section analysis, 横断面分析
, X3 P# a* P, vCross-section survey, 横断面调查, D# k- }; m7 P) l2 t
Crosstabs , 交叉表
+ l% a- V: T/ L* H( T2 S1 b6 _Cross-tabulation table, 复合表
% E7 I7 g0 {% D+ N1 Y! MCube root, 立方根
- j# P k2 ~/ uCumulative distribution function, 分布函数
" l) ]4 q7 D5 O, S2 m# w, v8 |Cumulative probability, 累计概率
0 g7 B8 y, ?, g( p' k7 FCurvature, 曲率/弯曲+ s0 T! X6 v0 r! U
Curvature, 曲率
( O, a* w! @) H. }3 m C7 g# q7 WCurve fit , 曲线拟和 & ]; R; S2 O; d1 u1 ]# n/ K; e* t
Curve fitting, 曲线拟合
5 h& T2 z$ Y) MCurvilinear regression, 曲线回归
" d) l" }' v9 {+ Z& R, zCurvilinear relation, 曲线关系) |: s7 w( y# h; m6 X& o
Cut-and-try method, 尝试法
" q+ p4 _- R& Q! z7 T; f) YCycle, 周期7 O3 F5 G7 X$ }7 C- P
Cyclist, 周期性
: m; A) T( j# n2 @4 rD test, D检验7 N6 z" l7 c7 `+ Z" Q
Data acquisition, 资料收集
$ J; W- G L& L5 n1 [& ^. nData bank, 数据库
$ a9 D( w" a3 SData capacity, 数据容量: m# Y( v7 T o. ]/ A
Data deficiencies, 数据缺乏
& f: |4 m# b5 _Data handling, 数据处理4 v3 T/ v$ Y( Y5 I/ `0 ]
Data manipulation, 数据处理1 m B" p3 m1 b5 m# S: }* m# N3 e
Data processing, 数据处理
7 e6 J1 i9 M# M* u& w" lData reduction, 数据缩减
+ Y- W& r+ w: M0 o- MData set, 数据集
1 g* z1 b& c, {3 m! K4 X lData sources, 数据来源
$ y. n$ g) X+ Y" \6 [$ x. lData transformation, 数据变换( O" b. ?2 g0 O' m
Data validity, 数据有效性4 Q/ E* B5 E8 q4 @4 ?+ m0 l c
Data-in, 数据输入
$ b. @) U& ?" Q& |: ^. XData-out, 数据输出
% t( G0 D& y+ H7 k3 y5 pDead time, 停滞期
0 s5 {4 h" C2 _/ y) N$ ^Degree of freedom, 自由度2 |, {9 a- O3 ` d- p1 H
Degree of precision, 精密度
* }3 h4 Z5 V7 r3 S! F1 h. DDegree of reliability, 可靠性程度
1 \5 r( S- K* U- i: RDegression, 递减
8 S$ a! @8 _% m2 PDensity function, 密度函数9 k! y/ t$ L0 }! P, z7 q' b9 h; n0 ?
Density of data points, 数据点的密度
! t8 E. D6 X; R6 \Dependent variable, 应变量/依变量/因变量
8 p5 |4 u$ U6 ` y! {3 c) k- YDependent variable, 因变量
# _1 t) {( C4 q& rDepth, 深度( z6 C) N" {# v
Derivative matrix, 导数矩阵
8 [1 B5 {& p/ X, h- I( HDerivative-free methods, 无导数方法3 t/ T: R1 D" _
Design, 设计
3 h* q$ v# C3 ^# Y0 MDeterminacy, 确定性
# {4 R, o; P% b0 I$ {4 x* ^8 \Determinant, 行列式7 s+ G% [- E: w8 b: ^1 U% a
Determinant, 决定因素% v7 j4 i1 Q9 K" R% P
Deviation, 离差6 ?" \- U6 W5 o) t- o+ ~
Deviation from average, 离均差1 e3 i* U- A8 |8 d& s) e0 S1 M
Diagnostic plot, 诊断图& g! W% X9 J* C8 }$ q5 r! {
Dichotomous variable, 二分变量$ N; T9 L- X( I% {
Differential equation, 微分方程
0 q- j% P0 {8 p: v+ QDirect standardization, 直接标准化法5 p# C$ J Q0 q3 q# y
Discrete variable, 离散型变量; i( ?$ }( M) K3 g" r v
DISCRIMINANT, 判断 8 G6 C& g b8 R
Discriminant analysis, 判别分析 r1 n O9 k+ C/ \
Discriminant coefficient, 判别系数
- L$ Z! ?/ M8 r7 l+ Z% sDiscriminant function, 判别值
3 T5 I8 c! r: ~2 E$ F* \) _Dispersion, 散布/分散度- ^1 h5 |7 w6 U& b' @1 |& b0 }+ W. v
Disproportional, 不成比例的
& C6 E( [; F! QDisproportionate sub-class numbers, 不成比例次级组含量
( @. ^8 z1 h/ l- kDistribution free, 分布无关性/免分布
/ d- e* o3 B. p* S4 t5 s/ u0 {Distribution shape, 分布形状
G: q V8 \& O; c& \. CDistribution-free method, 任意分布法7 }& I/ a; |( K) }! ]
Distributive laws, 分配律
( q/ v: ?% ~9 y" `Disturbance, 随机扰动项
2 a6 ?7 D' D- C9 uDose response curve, 剂量反应曲线+ t/ R4 G& B, i3 D! g; c& O
Double blind method, 双盲法4 ^( f4 g+ \% q' A% V
Double blind trial, 双盲试验1 V1 t; B1 c0 Q+ F& H8 ?$ t
Double exponential distribution, 双指数分布
3 B: M" c5 t- v) K6 |Double logarithmic, 双对数
( `& f8 \9 w, r5 uDownward rank, 降秩 ~- R/ Q6 T+ j
Dual-space plot, 对偶空间图
2 r; \' x: B! e4 ?6 \+ s; ODUD, 无导数方法
8 p* u8 f* P4 C' I% c ~" j7 mDuncan's new multiple range method, 新复极差法/Duncan新法: Z- e4 f( p8 t3 [9 P, N
Effect, 实验效应
7 _. i; L! F3 D& mEigenvalue, 特征值
6 Z$ k% M( O7 W' ^& AEigenvector, 特征向量
7 E3 U+ H m; I( ~9 Y8 j( KEllipse, 椭圆; E$ t" n) |7 P0 i6 s j
Empirical distribution, 经验分布
, I- K5 k: L& o* Q) @! u3 O) |Empirical probability, 经验概率单位
) y0 r& s# |5 }/ ]8 }, MEnumeration data, 计数资料
1 U X. Z2 `. q( F) mEqual sun-class number, 相等次级组含量7 W, n8 B# y# r% L
Equally likely, 等可能. Z9 d' u: y4 e5 h7 W6 h9 R
Equivariance, 同变性( t0 X4 r) y7 @* x' r5 f
Error, 误差/错误
# _' ~4 X5 e3 m# g+ c W3 D, @/ fError of estimate, 估计误差
( z+ n3 n- x+ ?5 k5 Y+ l. t% L7 w/ nError type I, 第一类错误
# U) ~1 A2 Z8 kError type II, 第二类错误
) B* D! H0 s: E5 SEstimand, 被估量
7 \& l' N6 @ }6 UEstimated error mean squares, 估计误差均方
- }, Y- {: u6 A9 N2 U9 REstimated error sum of squares, 估计误差平方和
& D8 I P3 g+ k2 \0 jEuclidean distance, 欧式距离$ O5 l2 F j( t" W
Event, 事件* A9 b+ n- s0 n; H1 S M
Event, 事件
' I4 h9 _% ~/ S: E& `$ tExceptional data point, 异常数据点
+ s3 C' l' E7 j' d. l. NExpectation plane, 期望平面
4 V0 Y5 ?5 G$ T3 B H+ b- ZExpectation surface, 期望曲面! `$ Q, h) C. Y+ I' R9 P9 c( X
Expected values, 期望值
9 Y$ w* Y4 j; f+ q$ p/ dExperiment, 实验
9 S# o" y% L! Q# z0 o9 nExperimental sampling, 试验抽样, V/ h* C0 F5 z1 Y1 `$ @* N
Experimental unit, 试验单位
7 y3 A8 _( v, q$ B: q, U& B! V& ~Explanatory variable, 说明变量 M& q! ?/ a5 K9 N8 F9 ] D4 L
Exploratory data analysis, 探索性数据分析
3 H7 P' H2 O0 J, ^- f4 i0 dExplore Summarize, 探索-摘要
. r8 o0 G* H7 h3 \7 ~% s4 E" GExponential curve, 指数曲线
+ H5 v4 N4 X& _' J6 xExponential growth, 指数式增长6 R& h: ] J3 H& r% `
EXSMOOTH, 指数平滑方法
! t0 _/ r4 y0 l' t% S: }7 EExtended fit, 扩充拟合. ]: C+ r8 Q# M9 V: \
Extra parameter, 附加参数
/ x" _; u0 }! x* E0 y: lExtrapolation, 外推法
' y) {5 D p; o6 l( _Extreme observation, 末端观测值4 M0 X( l, [% P( K! p4 X6 t
Extremes, 极端值/极值- N# [: b5 G2 z/ [: Z
F distribution, F分布4 a9 ?( Q) h7 l7 `2 x9 F6 Z
F test, F检验
# E p) n) x4 _' W) z6 w) dFactor, 因素/因子" }" v8 y# P# K& t9 r
Factor analysis, 因子分析. I( K9 F/ t8 d+ |- |1 S* D
Factor Analysis, 因子分析 i8 }) e2 O% Y9 {4 o# a9 ]
Factor score, 因子得分
/ u0 R1 _" p( Y; w4 JFactorial, 阶乘; N( {: Y" E) X3 h$ x
Factorial design, 析因试验设计% G! u, _3 M% t! O# t) H* f1 H4 h
False negative, 假阴性
8 G5 P( }- z0 ^8 rFalse negative error, 假阴性错误) Y9 K$ U: A$ z* h" s
Family of distributions, 分布族+ H4 Z/ K4 X5 y1 _" b6 b" h; N; F
Family of estimators, 估计量族
6 R6 ^( [, b7 B& x7 |Fanning, 扇面
" V) L9 L6 J) s+ l& yFatality rate, 病死率
9 D" p) g4 V/ P# }" r( ]Field investigation, 现场调查) J) y$ p8 x. P7 z, Q9 z
Field survey, 现场调查
- S. q" a4 S4 |Finite population, 有限总体6 b5 x( p1 P' C" y7 f# L6 D p. z/ Q
Finite-sample, 有限样本3 b7 U8 z; G% j/ n& U
First derivative, 一阶导数 n6 I4 X- h' m/ g
First principal component, 第一主成分
$ J1 u9 C$ w( c a3 DFirst quartile, 第一四分位数# \" g2 L/ d2 X( a' y# M$ V$ R
Fisher information, 费雪信息量
# w& H& ~0 {1 b TFitted value, 拟合值
, P- M( v. A" R' A. J+ GFitting a curve, 曲线拟合
- y9 C) O$ p# C, H CFixed base, 定基
4 w, n7 t* _# s1 nFluctuation, 随机起伏
3 K+ h8 A: Z. Y- x) t" `Forecast, 预测% B9 l9 S$ C$ ^3 i0 v: P
Four fold table, 四格表
4 C1 T- d) C, S. zFourth, 四分点
, A3 ^; e/ e) b+ t2 v6 dFraction blow, 左侧比率
* }6 r L! i, Z% i+ j) R+ cFractional error, 相对误差: j, |4 [" {- J' `/ R: Q$ J
Frequency, 频率" x( P2 H+ \; D: ?6 T2 O( `
Frequency polygon, 频数多边图
) e! ^+ p4 k2 C' _Frontier point, 界限点
. i. I( p" g0 s6 O7 C/ P2 x3 N5 J9 CFunction relationship, 泛函关系
& V$ D1 F. q4 o, T& j( EGamma distribution, 伽玛分布# v: W% `. M2 d, n z8 q2 J
Gauss increment, 高斯增量9 p) n/ O; l3 M+ m/ [( f0 `
Gaussian distribution, 高斯分布/正态分布- u z1 T0 u4 ]. j, ]
Gauss-Newton increment, 高斯-牛顿增量
( K. t/ k" m& y! D* e( S, _. ZGeneral census, 全面普查1 { g6 S( ~* s
GENLOG (Generalized liner models), 广义线性模型
5 z1 m1 x, h5 b4 @8 M+ r" W: RGeometric mean, 几何平均数
# V p) z# N6 v# \9 ?" M1 h6 ~Gini's mean difference, 基尼均差& {* Q6 ]7 Z5 u( H( A7 Z
GLM (General liner models), 一般线性模型
: w% H1 L# Z3 h. B/ M4 m; HGoodness of fit, 拟和优度/配合度
' J- t1 Z! d1 l5 ?: qGradient of determinant, 行列式的梯度
9 n$ _& A7 z. j7 [& h7 \: mGraeco-Latin square, 希腊拉丁方; s, C1 S. x+ w- a4 A! L6 ]3 B2 b; }, G
Grand mean, 总均值
+ V- z9 x9 h$ C0 f+ L. oGross errors, 重大错误% l: _; u) M7 F7 ?; b. K
Gross-error sensitivity, 大错敏感度. I! ~1 t# ^& ~7 S Q/ |+ Z. {" [
Group averages, 分组平均
' r9 I: i0 k( @Grouped data, 分组资料$ c9 d. {2 Q8 k
Guessed mean, 假定平均数
, M; K N# k6 {, G5 lHalf-life, 半衰期) f" ?" n3 D- `/ t' w
Hampel M-estimators, 汉佩尔M估计量9 s% l4 U; w- E0 v6 m- y9 `0 G" b
Happenstance, 偶然事件0 b" Q8 l% j9 M* ?4 [* Z( Y3 O
Harmonic mean, 调和均数2 M. R9 M! Y( i% ^! T
Hazard function, 风险均数
( @$ k" L! J8 U7 s# c* V! ZHazard rate, 风险率! Y4 p. v4 j" Q, q2 w6 Q
Heading, 标目 ) m [ |2 v. M) d, }
Heavy-tailed distribution, 重尾分布
' ~/ Y# C" m8 P) g! K+ s5 B; H7 X! dHessian array, 海森立体阵
# i2 S0 Y$ Q& q1 ?! ?' g; j2 ]Heterogeneity, 不同质" U2 w% y( \* T) R Q6 a, V
Heterogeneity of variance, 方差不齐 6 I8 a v/ Q. `% H2 G9 S& o' p
Hierarchical classification, 组内分组
% q! y, q' J: T% }, d7 hHierarchical clustering method, 系统聚类法 R% \3 k5 g4 w
High-leverage point, 高杠杆率点
4 w8 b& B0 M7 L/ k$ f" mHILOGLINEAR, 多维列联表的层次对数线性模型/ Z/ ?) t2 Z( ?0 _( }0 t
Hinge, 折叶点
- r( S2 u! ]! |. n9 Y+ AHistogram, 直方图
6 N; }$ |- s8 f- SHistorical cohort study, 历史性队列研究
6 @- V: r8 h. aHoles, 空洞1 K: a/ `: K# U, }- q
HOMALS, 多重响应分析
/ g: S: a6 C A6 v( h3 I1 aHomogeneity of variance, 方差齐性- [( C" R& c2 x9 F) I
Homogeneity test, 齐性检验
- }- L0 k0 f/ F6 cHuber M-estimators, 休伯M估计量+ Q2 o6 U8 W! I! y
Hyperbola, 双曲线
) Q- t+ d! ?1 O" [$ k+ Y/ aHypothesis testing, 假设检验* d! B. \/ Q6 P( ]5 L
Hypothetical universe, 假设总体9 t; i% Q' \: M6 u- |6 s8 g( V) X l8 W
Impossible event, 不可能事件' G* Q7 _& r4 F7 @
Independence, 独立性
. X; A; G7 f3 X$ Y1 P8 d. QIndependent variable, 自变量
+ c% |5 g0 g" K( m9 _8 R* j4 MIndex, 指标/指数
4 a( L- i9 b' f) zIndirect standardization, 间接标准化法
8 Z6 P' N# F9 ?( _Individual, 个体/ C# H, F9 r# q2 e% E/ O" g
Inference band, 推断带3 y( `, z& m1 U0 |9 h
Infinite population, 无限总体
4 G/ u$ P! ^ N: MInfinitely great, 无穷大2 {/ A: a+ I3 u8 g1 P+ z0 t
Infinitely small, 无穷小+ r2 e; ^6 b: m& u
Influence curve, 影响曲线# P6 u U, F/ g( ?/ n
Information capacity, 信息容量8 [) k' A) N: w9 H+ Q
Initial condition, 初始条件
* b1 K B9 u9 F% U. s1 _Initial estimate, 初始估计值
" r7 D+ f- e: _" }% NInitial level, 最初水平+ \/ Q5 z5 ]; b
Interaction, 交互作用
* }* Y3 |" D7 H# Y E+ KInteraction terms, 交互作用项" Z5 ^2 { {: ~, O* F
Intercept, 截距4 h+ \: O* ~. U
Interpolation, 内插法8 T' D Y8 G7 n% X; Y+ B* R# \
Interquartile range, 四分位距# n7 n3 n! R. V+ ~/ S) Q! I
Interval estimation, 区间估计5 ]8 p8 ~/ s) @3 k5 M7 s
Intervals of equal probability, 等概率区间
! u6 A4 O G1 g1 t8 RIntrinsic curvature, 固有曲率 x( S+ X5 m& i! _7 b' ^: w" Q
Invariance, 不变性
! H+ F7 m$ z/ j6 ?5 N7 }Inverse matrix, 逆矩阵
P+ H- L) M" @8 M( U# nInverse probability, 逆概率% _' s, m {& H: ^
Inverse sine transformation, 反正弦变换" u2 Z7 ^( [! t6 I; | ~
Iteration, 迭代
1 m% |4 B. y- f! i" g8 H/ j& ]Jacobian determinant, 雅可比行列式
6 s [4 _. B, @& XJoint distribution function, 分布函数+ i" \4 ~+ G8 a$ W- n& z3 p( f# y
Joint probability, 联合概率0 ~ R5 D2 {) f+ Y
Joint probability distribution, 联合概率分布) r, u6 R0 A" \1 T
K means method, 逐步聚类法! w7 t/ ~, |1 Q; t' @3 \
Kaplan-Meier, 评估事件的时间长度
9 A3 z3 f) l# o$ U' o' S7 Q7 D! WKaplan-Merier chart, Kaplan-Merier图
" @1 } U2 I1 t) \# z! V7 OKendall's rank correlation, Kendall等级相关
. v/ w q+ z, J% K6 nKinetic, 动力学
5 o1 c- K7 J$ x8 u) dKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
& k8 ?. f7 n/ S, _0 `5 eKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验2 M$ j( B, [9 f. Y* R
Kurtosis, 峰度+ U& c' N J" _2 B$ u
Lack of fit, 失拟+ ]/ d' ^0 i% g3 M( q S2 l
Ladder of powers, 幂阶梯7 O* G3 r; I* v% Q
Lag, 滞后
" v5 X' l. u- aLarge sample, 大样本8 x; ~* O- r! ~) ?! k8 F& j
Large sample test, 大样本检验
3 S* b& T# h5 }- rLatin square, 拉丁方
; @; d4 v* }1 f+ d" T; ^Latin square design, 拉丁方设计 N- c1 r" x- ]2 i; E
Leakage, 泄漏
/ d+ ?* y( N% E+ s9 zLeast favorable configuration, 最不利构形
9 m* X. T* ?5 B, I* A# p. ~# D$ pLeast favorable distribution, 最不利分布- p8 t, m8 Y' j2 C$ Y3 u
Least significant difference, 最小显著差法
# T" ^5 H9 S8 f! @Least square method, 最小二乘法& ?0 F B" ~% l, P' @
Least-absolute-residuals estimates, 最小绝对残差估计
) b1 r+ w6 r- u9 e$ P. GLeast-absolute-residuals fit, 最小绝对残差拟合6 I! m* P9 i0 X$ ~1 Z3 ]
Least-absolute-residuals line, 最小绝对残差线% n4 f7 B' E( k% ~, v! y" P
Legend, 图例; r0 V3 c) t3 j' t+ B/ j
L-estimator, L估计量
9 z- Y7 X. \0 tL-estimator of location, 位置L估计量, W8 o: V& ?: p: f, f; J3 ~
L-estimator of scale, 尺度L估计量
( [* S8 \9 h# PLevel, 水平- Z! A# _% o. |# Q5 t
Life expectance, 预期期望寿命8 H& I+ ~6 S/ |6 l3 q" i
Life table, 寿命表
4 R5 O( N& h- x1 Y N3 Y- mLife table method, 生命表法( x9 f" X z0 S6 C4 O. K
Light-tailed distribution, 轻尾分布/ w7 E) _: p, H# _
Likelihood function, 似然函数
4 ^2 j: |' Y# I4 U: c6 k KLikelihood ratio, 似然比
5 H: T5 V* P' fline graph, 线图" [! j+ ?, V6 M8 N+ y1 \. Z
Linear correlation, 直线相关
$ K; G! V( f8 j* [Linear equation, 线性方程
# ^- I8 C" n Q8 c1 S" N# ^Linear programming, 线性规划
5 X0 v. @1 @( e3 Y( X. K- j% |Linear regression, 直线回归
0 ?# y, R1 p" G( N/ [ GLinear Regression, 线性回归
, B7 W1 r4 K/ \8 f* F# x/ \: e6 v& {) xLinear trend, 线性趋势' w* @/ h6 m+ a
Loading, 载荷
1 M, c: G" W. v4 t( oLocation and scale equivariance, 位置尺度同变性
! r; v& R4 Q; w! [! Z" f* uLocation equivariance, 位置同变性 H. m& |. D% Q4 S8 b! ^
Location invariance, 位置不变性
& g e* w! l) `6 ZLocation scale family, 位置尺度族7 S- Y2 w$ x, C+ b1 c
Log rank test, 时序检验
& A" h7 ~3 M1 f" @; W kLogarithmic curve, 对数曲线
: U% c& R2 d' V; E. ?" ]Logarithmic normal distribution, 对数正态分布
+ k: L5 O6 j/ `6 T5 Q8 [Logarithmic scale, 对数尺度2 x, r; m4 q1 p* a' |6 b$ V
Logarithmic transformation, 对数变换( C; |/ N+ g6 j j" |+ _- o
Logic check, 逻辑检查
% D* \6 O7 l" R+ s. m1 S* }, a5 pLogistic distribution, 逻辑斯特分布. o! z. v# n' a, M$ G) k* j" e
Logit transformation, Logit转换* @# F- v* o) T( J; F- p7 r% T% U
LOGLINEAR, 多维列联表通用模型
! n" @. n9 i) ]) \0 e+ H" B! I, VLognormal distribution, 对数正态分布
& X6 d3 H8 L$ o2 u2 |# v. qLost function, 损失函数/ {$ X3 G9 Z, R9 U$ O
Low correlation, 低度相关6 V. r8 c! z4 F' a- [: m5 ]; O
Lower limit, 下限+ E, h" G5 `8 U/ H5 Q2 w
Lowest-attained variance, 最小可达方差6 t2 K5 f( o2 U
LSD, 最小显著差法的简称
" K0 O5 c6 [% H `( ZLurking variable, 潜在变量. k, |6 c4 Z$ @/ g' L6 `
Main effect, 主效应9 M5 a* i1 V6 T3 G
Major heading, 主辞标目5 \: B+ Y7 U" M- l
Marginal density function, 边缘密度函数, N: C9 Y0 K3 c( a1 x: _" G& y7 v/ D
Marginal probability, 边缘概率+ o( W5 \7 s, E
Marginal probability distribution, 边缘概率分布
6 m; i% u. }: h3 z5 S& | N! W0 sMatched data, 配对资料
- c, R* X; \1 h) wMatched distribution, 匹配过分布0 a( t8 p2 M' J3 }
Matching of distribution, 分布的匹配
3 n' R1 F* v" L' ?Matching of transformation, 变换的匹配
) E2 o$ G9 i, ^0 k2 b5 s4 @- E EMathematical expectation, 数学期望# @/ e5 l. r0 p) R/ \
Mathematical model, 数学模型5 u4 i, h) ] D" h. ~
Maximum L-estimator, 极大极小L 估计量" W, M, B/ S0 p( e3 U0 X1 N
Maximum likelihood method, 最大似然法" f6 T8 M* v* @( w+ M. ~. H
Mean, 均数
# \- d8 U) t, D, ^0 i @( m. TMean squares between groups, 组间均方
+ N$ @* J% V0 A/ w7 j! GMean squares within group, 组内均方
6 O% p$ Q/ I$ h9 {6 o* }Means (Compare means), 均值-均值比较" J6 m" g: @6 p- H& d, d* \
Median, 中位数
5 `0 M( [) g! b- Z) t- ]Median effective dose, 半数效量( ?1 M+ V: `; ^
Median lethal dose, 半数致死量
0 g0 g7 B$ N4 k: aMedian polish, 中位数平滑
+ k0 g" `$ F& ?8 w# w5 {Median test, 中位数检验5 f2 J% [; k: T; x9 S$ X
Minimal sufficient statistic, 最小充分统计量# x! O5 U# ]# v' ]
Minimum distance estimation, 最小距离估计) u! Z+ R* M3 z/ L! \$ E
Minimum effective dose, 最小有效量- f; W( x* h* }" X; `6 g
Minimum lethal dose, 最小致死量
& n: F# t& i/ O8 G5 U! AMinimum variance estimator, 最小方差估计量
7 Z( ]9 F: T0 X3 ] D0 j, A. F* v5 \6 IMINITAB, 统计软件包1 B$ g5 l+ F- N H6 Z
Minor heading, 宾词标目
: [8 V* P9 s0 [. l! d4 aMissing data, 缺失值 Z( v2 j% a% Z
Model specification, 模型的确定
5 `( s7 S1 {; g' j8 f2 d: V# KModeling Statistics , 模型统计" H; L& w0 d7 }! Z K
Models for outliers, 离群值模型
" O3 z2 G- j, \3 }; YModifying the model, 模型的修正3 n) S! \( ?! B! u L$ T
Modulus of continuity, 连续性模! X* k, j# t7 C- i' L8 e! ^
Morbidity, 发病率 # V: b& W: _1 n5 F
Most favorable configuration, 最有利构形
+ }3 {/ ^4 \" Z* pMultidimensional Scaling (ASCAL), 多维尺度/多维标度* r: S& e+ I5 t2 W( B+ [2 C
Multinomial Logistic Regression , 多项逻辑斯蒂回归5 p8 f" \9 O/ z4 s9 d( F- C
Multiple comparison, 多重比较% f4 o- [/ [! N, a; K# N5 b2 P( M
Multiple correlation , 复相关
& U. Y' y+ G/ m* ]8 pMultiple covariance, 多元协方差- _5 [+ E* B6 Z0 b/ _4 C. |
Multiple linear regression, 多元线性回归. H6 C. F9 D% L/ ^6 C$ m3 R
Multiple response , 多重选项2 }* P' v& b8 H( U; p& g5 \( y6 b
Multiple solutions, 多解# J3 C$ O8 K; A8 h1 z0 b
Multiplication theorem, 乘法定理
- H2 w6 P& _+ d8 j! K0 I% EMultiresponse, 多元响应) C' I# P3 @2 M! E# P _ B: i
Multi-stage sampling, 多阶段抽样
0 y6 r" Z$ U$ U6 x; LMultivariate T distribution, 多元T分布1 D9 q4 H1 e- ]; v" R
Mutual exclusive, 互不相容1 K$ ^6 X4 t% ^8 j
Mutual independence, 互相独立
. R0 ]+ e0 e e, }: b: [, PNatural boundary, 自然边界4 ~# l, K, f4 w5 k: J
Natural dead, 自然死亡) \4 B( `+ y2 W
Natural zero, 自然零
+ s! q/ k _7 L- S2 M4 e! qNegative correlation, 负相关: s3 \/ X6 r9 m$ Y
Negative linear correlation, 负线性相关
. e( U, a* I' B$ w5 E9 MNegatively skewed, 负偏
$ ~# L" d* M. I& a& vNewman-Keuls method, q检验0 V2 i# r8 C: ?
NK method, q检验
( y; p% {6 I6 ]( K8 {1 xNo statistical significance, 无统计意义
3 x1 P: n5 y& M# a9 W' L- k LNominal variable, 名义变量
9 O" K- n% v. e" n r# vNonconstancy of variability, 变异的非定常性
) f ?5 Y& Z1 S# v2 e9 W2 \4 JNonlinear regression, 非线性相关( Y7 d0 O" S' l0 f
Nonparametric statistics, 非参数统计) v8 P/ I; ~6 w
Nonparametric test, 非参数检验
! v5 C: i# [4 y5 C+ | U4 CNonparametric tests, 非参数检验
9 P4 L: x( k9 p: c1 qNormal deviate, 正态离差
0 t9 N1 u* j! R, G- t; T {: zNormal distribution, 正态分布
; j, u- J" K6 C% R; l! r& T0 qNormal equation, 正规方程组0 n) a' i; U* D: Y3 d. @
Normal ranges, 正常范围
; R. S& h- P- g- s m" _2 |8 R. @ ^, tNormal value, 正常值: e; l2 r; Y7 }& W: S; b' E
Nuisance parameter, 多余参数/讨厌参数) F% x. N, W) o0 @/ O
Null hypothesis, 无效假设
! t! N& F4 b5 D* PNumerical variable, 数值变量
' {6 H: P' G2 c7 A2 @7 C! lObjective function, 目标函数
0 r" N0 |- E$ R s/ iObservation unit, 观察单位6 @5 y+ P) Z1 z% g' j0 J- g" t: C
Observed value, 观察值
# d% ?6 G% ^! j% w9 \One sided test, 单侧检验% e m: }# k3 {- S! U/ @
One-way analysis of variance, 单因素方差分析
; {% T" Z# m2 R p# h" UOneway ANOVA , 单因素方差分析 z6 m1 x, f' A; n. W/ T0 u
Open sequential trial, 开放型序贯设计, l; x$ _2 j0 Q/ I, U3 ~/ e
Optrim, 优切尾7 U+ {. H' {9 c8 N3 c8 E* ~, v
Optrim efficiency, 优切尾效率
/ a/ ^; w& T3 l6 dOrder statistics, 顺序统计量9 r/ o6 R) Q9 F, w: V5 q1 r6 P, |
Ordered categories, 有序分类
: W; b2 ?' Y- l! H% mOrdinal logistic regression , 序数逻辑斯蒂回归 [6 x8 m" w# e: R! b6 b9 ~* }: ~3 T
Ordinal variable, 有序变量) X/ z! E H; ]% q$ F# E
Orthogonal basis, 正交基
3 i2 {5 d9 l+ F+ J' qOrthogonal design, 正交试验设计
$ j2 _* m" o1 E6 POrthogonality conditions, 正交条件" e7 K k' z* n: ]4 Y: I+ e P/ h
ORTHOPLAN, 正交设计
: u( z0 {( X( e+ o; y# z: ?- AOutlier cutoffs, 离群值截断点7 _) c& r0 q8 l7 g/ J
Outliers, 极端值( g! ~, k& i! }. a! P
OVERALS , 多组变量的非线性正规相关 1 b M9 z2 ]) d& C0 z4 t& D
Overshoot, 迭代过度$ n) M. l! a/ m9 n
Paired design, 配对设计) R" v g, A5 u R8 ?8 v2 U
Paired sample, 配对样本
, ~3 l5 b9 \' MPairwise slopes, 成对斜率
2 y/ k0 m5 K' `: k0 @" T* KParabola, 抛物线
7 [- | U x5 O8 eParallel tests, 平行试验+ C3 G' W2 P% n& g u
Parameter, 参数
, j" R+ H2 Z' M% a7 B nParametric statistics, 参数统计
8 `% |% q1 Q$ T3 b! o; }' l) b8 }Parametric test, 参数检验
, J2 S" L) r' h7 k3 \4 ePartial correlation, 偏相关/ x. C9 f4 _: R3 |& Y- o4 y
Partial regression, 偏回归
2 J' Y6 t1 J) X# IPartial sorting, 偏排序
( d/ h+ e6 R$ _+ y+ F% oPartials residuals, 偏残差
& p2 b) [ ~# }+ I7 rPattern, 模式: c V L( @8 m1 V- G% q- W# _
Pearson curves, 皮尔逊曲线# |3 K9 n2 q: u* p: w
Peeling, 退层
k; M0 O Y9 n9 jPercent bar graph, 百分条形图6 O: a V4 y- l& H( \$ m" }
Percentage, 百分比
( E9 u0 F' l. Z4 \, d+ s1 kPercentile, 百分位数
4 @( W5 V- k) R* G* _" Z7 T+ DPercentile curves, 百分位曲线( S0 k# i* {1 l7 _. l8 {3 D* w
Periodicity, 周期性1 r" G4 o4 @( S2 }: N& A5 f
Permutation, 排列 A& ^! o9 U* x
P-estimator, P估计量) M, q$ J: V. O! W( n6 I* S( A
Pie graph, 饼图
8 I! w& C) L s2 r: k+ MPitman estimator, 皮特曼估计量
% } O! x! G0 F* o, m, G+ ? sPivot, 枢轴量
0 C# l7 o" x6 K2 ` aPlanar, 平坦
% y$ x K, _. x! X' L* {: XPlanar assumption, 平面的假设
! q) @3 [! J7 q B1 @# {1 ?PLANCARDS, 生成试验的计划卡
0 t- x5 i& \; _9 H4 j1 XPoint estimation, 点估计
. H4 G0 X( {% ~7 CPoisson distribution, 泊松分布
: A: P* ]- q$ S' PPolishing, 平滑
' A j" b$ F8 P k8 _Polled standard deviation, 合并标准差
" w% m3 [9 G6 k( L0 c Q' LPolled variance, 合并方差4 z$ k' r2 @( b# [( D @' d: y
Polygon, 多边图
/ R9 N" Z8 g( u: y% V- dPolynomial, 多项式
$ {5 }/ ?9 F& `Polynomial curve, 多项式曲线
: S! U @& W' s$ ^5 J6 KPopulation, 总体
0 A8 F+ }& }7 I# f+ c7 cPopulation attributable risk, 人群归因危险度* m& K8 _4 {7 c- L+ O# s5 Q- A
Positive correlation, 正相关
+ L5 e/ s M8 t9 B2 O% jPositively skewed, 正偏
1 T: \7 Y( E+ h b" I' [ [Posterior distribution, 后验分布- ?7 M ?+ w% {7 k7 W( M
Power of a test, 检验效能
8 _* r" L. `2 \" `8 d; bPrecision, 精密度5 w1 J2 K- K5 N- e# O
Predicted value, 预测值
5 v! h/ _4 h$ k8 i/ h7 {0 r6 ZPreliminary analysis, 预备性分析9 {0 o: l; s2 L+ {! @# I
Principal component analysis, 主成分分析7 ^7 c3 n* P$ L
Prior distribution, 先验分布( Q" P7 D0 E# p
Prior probability, 先验概率
# N. W' ~0 X: }2 x$ n/ tProbabilistic model, 概率模型- I3 D9 x6 A3 d
probability, 概率% I3 X) @7 N1 A" x j# O0 B
Probability density, 概率密度; z# m. g0 R+ k; R
Product moment, 乘积矩/协方差9 D& H1 a* q- l- X+ @& F
Profile trace, 截面迹图& K. K/ M! ]7 w/ ]! P
Proportion, 比/构成比
# u4 A# {. \ [# z) n4 }8 KProportion allocation in stratified random sampling, 按比例分层随机抽样
! o! \' V; w2 f2 |8 B* FProportionate, 成比例
. z+ ?6 \# d: P q0 S. zProportionate sub-class numbers, 成比例次级组含量) S6 ~6 [7 ]+ ~9 Q/ L
Prospective study, 前瞻性调查
1 D, \+ j3 T3 b+ gProximities, 亲近性
, r- e4 r1 X M* D" {9 CPseudo F test, 近似F检验* E" h* l, C3 N) {- O4 w& l" }
Pseudo model, 近似模型( l0 ?* f2 w0 Y1 I
Pseudosigma, 伪标准差: M( {) @1 d2 Y- [
Purposive sampling, 有目的抽样5 i5 E2 {+ }8 l5 H' ?% l9 P
QR decomposition, QR分解( e( X/ b# g3 m9 z7 g- ?+ e
Quadratic approximation, 二次近似
) C- J: ?4 h! [; d$ jQualitative classification, 属性分类' _' g3 b8 c. e: R
Qualitative method, 定性方法( b3 N* Q" y, F6 k9 ]6 L
Quantile-quantile plot, 分位数-分位数图/Q-Q图
% T) {2 G d# w% A$ g5 Q5 OQuantitative analysis, 定量分析
+ W! T7 F; X/ i9 ^* f! FQuartile, 四分位数$ a6 R8 n2 l, M, |% L
Quick Cluster, 快速聚类
E" N' q4 @/ }" Z& B/ N. kRadix sort, 基数排序
6 F5 `0 d0 W- [3 QRandom allocation, 随机化分组
- A) T( _$ Z4 A0 a1 @5 q2 dRandom blocks design, 随机区组设计1 Y/ i4 }$ {3 Y+ P. {1 ?
Random event, 随机事件
/ X4 {! t9 r- E! ^* _Randomization, 随机化
7 d0 p0 `0 u5 x s( b6 [Range, 极差/全距
/ q% k) y# L4 e. I; t* S6 ~+ vRank correlation, 等级相关
# P% P, g0 S) Q8 |/ U& kRank sum test, 秩和检验6 Q \- M! w6 I& J
Rank test, 秩检验
" r1 I$ ^- i. s+ K. _Ranked data, 等级资料
h, K$ H" z2 c" M* C% e$ y& uRate, 比率- u& M$ N& m$ ]
Ratio, 比例
6 V- v8 C. A. e1 P# l ERaw data, 原始资料# V8 w2 V- G1 B
Raw residual, 原始残差
+ D6 ?/ F: h0 F0 CRayleigh's test, 雷氏检验: _) R1 H: O2 R, M5 S5 Y
Rayleigh's Z, 雷氏Z值 * i# k i9 ~( ]& b q
Reciprocal, 倒数
8 Z' C y% [: |/ Q/ s8 q3 {2 ^# K; @Reciprocal transformation, 倒数变换
- S8 x5 k: l0 x! [2 T- e9 YRecording, 记录- K+ Z h# T8 ~! p" w1 F0 e1 f
Redescending estimators, 回降估计量
) ^% g, M( [8 f" ]Reducing dimensions, 降维& p1 z: n' R8 n$ j/ t; F
Re-expression, 重新表达
: D! \. ?+ `) ^4 Z, EReference set, 标准组$ K, r, ?; I! ^5 m$ ], Z
Region of acceptance, 接受域
) E0 V! v4 v, n+ w LRegression coefficient, 回归系数! S$ k& I; [( S6 N
Regression sum of square, 回归平方和
, a0 A. ^7 ], X9 g- b: J% FRejection point, 拒绝点 y& U, ?# K, T2 K+ w
Relative dispersion, 相对离散度" D1 j0 y; v& t
Relative number, 相对数' p% X) r0 o4 a
Reliability, 可靠性& G+ r% b7 S, Q$ W- \
Reparametrization, 重新设置参数/ o% W, J2 q* T1 `- ^, \
Replication, 重复
1 P8 B9 W ?/ a# NReport Summaries, 报告摘要
5 w' l' g, `3 b8 J5 L# T) g) N% VResidual sum of square, 剩余平方和6 T; B O" r- @; {" c7 ^
Resistance, 耐抗性
2 P) o3 x% |" E& Y. W& QResistant line, 耐抗线
( y. D0 b/ l, n9 V1 \$ b1 @. u YResistant technique, 耐抗技术! p% r, M/ }: ~' _7 \
R-estimator of location, 位置R估计量& c1 L5 k, O5 P& V& V) m9 V- {) T
R-estimator of scale, 尺度R估计量6 Q( f+ d: e5 J$ j( U) p) @6 f
Retrospective study, 回顾性调查
2 x( \/ B& ~- BRidge trace, 岭迹 W% ?. q' _8 A, Y* z
Ridit analysis, Ridit分析3 o' Y) O+ C* Y7 ?* \; ]8 {& H
Rotation, 旋转
D7 x- E+ Z0 Z+ TRounding, 舍入
( O1 t c1 T0 N8 V# U3 yRow, 行
+ _+ |+ A% p3 k# x& |6 SRow effects, 行效应 [$ |- R( C( T/ t3 N3 F# U
Row factor, 行因素) x; Z2 ~3 m: V
RXC table, RXC表
- E; Z8 s7 B& bSample, 样本0 \4 Z% c3 [# s) i, k3 M
Sample regression coefficient, 样本回归系数
9 l+ x* b5 X7 f( V' wSample size, 样本量
" S! t4 O3 \ x* H: WSample standard deviation, 样本标准差" z! ]0 I. J1 g- @& ?9 ^) L
Sampling error, 抽样误差2 N% t: a* @4 T# g$ l, J
SAS(Statistical analysis system ), SAS统计软件包
- V3 V) p C0 ^+ p% S6 sScale, 尺度/量表
! S7 i# x8 K0 Y3 @2 Y, t" Y# [Scatter diagram, 散点图
! M6 e) w9 @. Q* a3 C; t' I0 dSchematic plot, 示意图/简图0 ~9 Q! O9 c- ^, I% c
Score test, 计分检验
" j# r% D6 f4 z+ x' r& \5 KScreening, 筛检, Q A- ^ F6 W M8 S" C, b& Z* L8 S3 ]
SEASON, 季节分析 - `; |; e X) s
Second derivative, 二阶导数
* g* k" P U) J6 xSecond principal component, 第二主成分8 e- X9 L2 Y8 R+ M* p
SEM (Structural equation modeling), 结构化方程模型 5 f8 x& a1 s: V. S: O3 W2 m
Semi-logarithmic graph, 半对数图! p. e y0 |) k% y! ?8 [
Semi-logarithmic paper, 半对数格纸( e/ d! _/ V: }7 i
Sensitivity curve, 敏感度曲线
- B, D# o. L1 e: ]0 v, HSequential analysis, 贯序分析
6 F' {! x: e* B% G) X+ `. uSequential data set, 顺序数据集
( r8 Z" \8 `) RSequential design, 贯序设计+ g0 \$ U+ g- F/ W) D! u
Sequential method, 贯序法9 J3 D: u% c) P. r/ n& v" x
Sequential test, 贯序检验法: V" @" O; F3 x
Serial tests, 系列试验. M" S7 m# U, [: U
Short-cut method, 简捷法 6 r4 t! ^7 I' }. K; A
Sigmoid curve, S形曲线
: u5 ^. ?4 B( K! r+ P3 KSign function, 正负号函数: j2 R( @, n# ~1 B; b
Sign test, 符号检验
; Z: P5 a. A$ z, m9 @' lSigned rank, 符号秩* y8 n0 ]* {, A$ a- J
Significance test, 显著性检验
( F, K4 }( v8 J: c* p- sSignificant figure, 有效数字! G5 q! _/ I' k! M# ]
Simple cluster sampling, 简单整群抽样. H' q/ T7 K' B" b7 `2 C
Simple correlation, 简单相关
7 b- o2 `! S7 y$ _Simple random sampling, 简单随机抽样( A' l0 Z* X1 Z, U X
Simple regression, 简单回归
- z$ e: K' G# J/ b& Y( csimple table, 简单表
5 c! U) x/ x( U7 L% ASine estimator, 正弦估计量
+ d7 Y3 x8 R# g/ z: c; J! QSingle-valued estimate, 单值估计
% _" ~( l& @2 W0 x5 [2 kSingular matrix, 奇异矩阵
6 g% Z. V% Z( m5 ZSkewed distribution, 偏斜分布/ b! s! }! N8 s3 ^
Skewness, 偏度3 V7 M! Q% |# y
Slash distribution, 斜线分布
, ?! l" S1 F e4 N, L' L1 @Slope, 斜率. ]& ~: S& p8 c7 B% ]$ s1 T( k5 f5 x+ |
Smirnov test, 斯米尔诺夫检验5 Z- `1 ^1 Q- W5 R
Source of variation, 变异来源
& j5 |; k B( C& e, v' JSpearman rank correlation, 斯皮尔曼等级相关( }3 j* x; g# a$ ^/ a) e0 Y
Specific factor, 特殊因子
2 D& h$ W( s( u q0 q$ I: K1 L/ xSpecific factor variance, 特殊因子方差5 b/ n5 e3 ?0 n. o# e. M0 |2 b! v/ X
Spectra , 频谱
' j1 b' @8 s- ?/ K& c4 Q4 [# h CSpherical distribution, 球型正态分布 J$ |& M9 `5 Z/ e/ c
Spread, 展布
; O1 Y6 G5 c. ]7 V7 BSPSS(Statistical package for the social science), SPSS统计软件包
) @% I- B! T. I( V$ ISpurious correlation, 假性相关
/ x n" p S- L0 K7 |, |5 aSquare root transformation, 平方根变换5 F2 E- G- _: n0 N% @, H$ }# R: r5 y
Stabilizing variance, 稳定方差
5 v a/ B: w6 b( T. Q; aStandard deviation, 标准差. K; P0 T7 K. p/ M# X4 V
Standard error, 标准误
+ x, ]/ c3 j: Q% B8 i- S+ h& }8 x+ }" RStandard error of difference, 差别的标准误
4 o L, [0 N' G9 c! vStandard error of estimate, 标准估计误差
; T5 o& X5 T7 w2 V" _* CStandard error of rate, 率的标准误
, a) a. n8 B, i7 L) d C$ S2 k+ wStandard normal distribution, 标准正态分布
: H. H/ [6 v' i) DStandardization, 标准化
: f9 V) f1 ?1 R8 U1 e$ C! RStarting value, 起始值
1 v2 A! w" f8 X$ v: G* c9 AStatistic, 统计量/ Z5 X$ _* j/ {5 f
Statistical control, 统计控制, P6 u, I4 |; V" N
Statistical graph, 统计图3 p; a, o; I1 f
Statistical inference, 统计推断" z/ M4 u/ t7 G- D5 S! p: l
Statistical table, 统计表
) D( s4 ~* t3 l) m& _Steepest descent, 最速下降法# ~ K/ Q l( @) a1 h
Stem and leaf display, 茎叶图3 |4 ^. O) n9 s: Z! C* t
Step factor, 步长因子7 z# q( J& H* B$ _! g
Stepwise regression, 逐步回归4 X+ d i6 M# u
Storage, 存
) b _4 T6 p5 ^; \$ WStrata, 层(复数)# O# h. w }7 l
Stratified sampling, 分层抽样$ M) N: W2 I& V( z7 [5 ^
Stratified sampling, 分层抽样
& g5 E* p5 J" ?! D( AStrength, 强度: ~1 {3 p4 s- B0 _
Stringency, 严密性, ^$ C! _: l, H: B! O
Structural relationship, 结构关系
, B( X1 U" l$ n& `5 w3 @0 B; [8 oStudentized residual, 学生化残差/t化残差& z& m9 A. t3 J p& M# i3 f
Sub-class numbers, 次级组含量& A( O4 w l) {
Subdividing, 分割
H1 M8 r% a7 |, a2 SSufficient statistic, 充分统计量" b* q7 k4 |2 }' {! ~, m4 D
Sum of products, 积和
s6 { {5 B4 \Sum of squares, 离差平方和
- ]0 P& F* O0 \! }* {0 CSum of squares about regression, 回归平方和
& u; ~) ^& D' t. X6 j( HSum of squares between groups, 组间平方和
; p2 B+ m/ h; j* xSum of squares of partial regression, 偏回归平方和
& A% {, {% Z2 [! m6 aSure event, 必然事件
- F* \7 R: m8 J& ?/ {Survey, 调查 ?: O& H" T1 j Y7 @
Survival, 生存分析
' N! |: R; U% U+ R6 G0 X4 ?- w3 {Survival rate, 生存率
* _1 J( G- d1 B" k/ k+ M$ l) VSuspended root gram, 悬吊根图
0 g0 S5 a* Y, }4 g; ~Symmetry, 对称6 ]' i8 G2 A; I0 q
Systematic error, 系统误差" a' Z) _4 g8 `& \+ r$ F
Systematic sampling, 系统抽样6 ~; C+ y2 q+ E ^4 E6 ]& `4 M8 U* T- k
Tags, 标签
: Y: ]0 Z7 w$ S0 oTail area, 尾部面积
4 h- {+ X( v' I. T7 RTail length, 尾长
2 v4 J# `% h7 L. g: V( x; i2 U. bTail weight, 尾重
) V% L. a2 }: qTangent line, 切线
, |$ b" K6 G" }Target distribution, 目标分布1 \- C( S9 n) D% J5 |8 B& h
Taylor series, 泰勒级数! {& n- a+ X O
Tendency of dispersion, 离散趋势
P. k4 o9 q+ J" u4 \Testing of hypotheses, 假设检验0 E; w+ ~' N8 w1 ~
Theoretical frequency, 理论频数
/ a* ~$ y' B, @7 _# f# G8 }Time series, 时间序列& q9 A# k( [; n/ r
Tolerance interval, 容忍区间
" }8 g( Z! [" m$ ~7 ?Tolerance lower limit, 容忍下限
1 A R4 I( Z$ }9 @( T& _Tolerance upper limit, 容忍上限
; y4 q Q' P1 n6 b! pTorsion, 扰率$ G; k$ `& P' ^+ }+ r4 w
Total sum of square, 总平方和. ^7 K: N- j" y+ u. x6 _8 I; h4 X
Total variation, 总变异
8 _ v9 E3 N! s( J9 G6 xTransformation, 转换
/ f! z2 o# j8 s! m" v+ `Treatment, 处理
: p4 n/ Z; h3 a+ QTrend, 趋势2 L t# ~3 M# k$ b7 s* Q# ]4 e9 E3 T. V
Trend of percentage, 百分比趋势
! ^- f, W& d. x/ s) ^% }, YTrial, 试验* ~1 `& H7 I# b3 T& b
Trial and error method, 试错法
: w9 k: K8 E5 q3 ITuning constant, 细调常数/ b1 i- Y- I% b/ ]; W5 r1 I$ D( w
Two sided test, 双向检验
. ~& Z" U/ t2 I5 n' fTwo-stage least squares, 二阶最小平方8 X" i5 q) @* K- O$ F
Two-stage sampling, 二阶段抽样
, s8 z3 \+ G" b( u# W! @+ q5 hTwo-tailed test, 双侧检验3 k4 k+ q' ?3 T& k6 _
Two-way analysis of variance, 双因素方差分析( ~4 V2 |, ^* S' p1 A
Two-way table, 双向表) k/ v+ l% X. s. f* H$ `, W1 ]
Type I error, 一类错误/α错误
3 Q6 c" ~3 z& @; A/ G0 zType II error, 二类错误/β错误
) _" F* O5 h6 m* ~ b. oUMVU, 方差一致最小无偏估计简称5 i1 b8 t$ _8 S8 r3 |
Unbiased estimate, 无偏估计
' J! x9 P5 [: L' U3 A" f% MUnconstrained nonlinear regression , 无约束非线性回归* [' t& h/ t/ [# n' P6 H2 ?( H
Unequal subclass number, 不等次级组含量0 ]+ y5 Q/ V0 Q$ C: j
Ungrouped data, 不分组资料1 _* m" g: F5 O8 K; X
Uniform coordinate, 均匀坐标
/ w N$ s6 ?1 H% eUniform distribution, 均匀分布
; V3 o* N- h- N5 m3 oUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
6 n& z2 D' \" v, sUnit, 单元
2 v! ^5 V8 O' W' }7 @) CUnordered categories, 无序分类
. F# g5 D2 H: u5 U Z pUpper limit, 上限
' N) T* h3 S4 m+ h0 eUpward rank, 升秩% U! l( D: p( ]; l* N9 N4 \
Vague concept, 模糊概念/ {; Q: A0 ?, v7 ?1 B* i
Validity, 有效性
% L* s/ B4 b( U0 Z& K/ ]+ dVARCOMP (Variance component estimation), 方差元素估计3 j# p- x4 u6 H |- M
Variability, 变异性+ v( o! o1 V+ n. U! {% ^
Variable, 变量
; _: q% F ?- C4 jVariance, 方差
* K6 `/ z6 O3 P. `* f$ lVariation, 变异) e% w8 `' i! V6 }
Varimax orthogonal rotation, 方差最大正交旋转
1 _7 I$ ]" l' ~3 x+ p% |* F6 Q7 {Volume of distribution, 容积* E5 Q" S2 n; h* _6 f! i, K
W test, W检验
- L) t; B' H# K7 @5 |Weibull distribution, 威布尔分布
: R' h p& Z7 w) C) `' OWeight, 权数% M4 }) Z5 x& L4 Y
Weighted Chi-square test, 加权卡方检验/Cochran检验1 d6 K" a. W6 Q! a% V2 z* V1 ?
Weighted linear regression method, 加权直线回归
$ W9 R& y9 @& F9 g5 G% WWeighted mean, 加权平均数
: U3 {* B6 J6 _! s* J+ f9 \Weighted mean square, 加权平均方差* ~; g0 j/ ~( a7 I" z
Weighted sum of square, 加权平方和
) a, b1 C4 r# R" `, }! Z9 G/ yWeighting coefficient, 权重系数" J# B" z: |0 Y" L; I
Weighting method, 加权法
. v% r8 |5 C" z5 w% A+ sW-estimation, W估计量
; a& |7 M0 C& X; x1 V/ L( o" oW-estimation of location, 位置W估计量3 x& `' C4 P6 P8 G
Width, 宽度
- C# x* h0 P. _* A" w) mWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
% G" P5 ~/ R* V$ @8 RWild point, 野点/狂点
$ k2 Y) k: L6 ]: ZWild value, 野值/狂值/ n6 l0 I( I+ c2 ~9 q# a
Winsorized mean, 缩尾均值
2 E3 B/ H& N, X/ UWithdraw, 失访 . _6 B& S' z" x/ r4 i. r
Youden's index, 尤登指数. s: h8 {* I& u- V1 Q5 i
Z test, Z检验
: [' Q N& [ x7 D4 ]9 }Zero correlation, 零相关
4 J+ `# f9 m7 z: c0 `# CZ-transformation, Z变换 |
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